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- Tasks: Lead a dynamic analytics engineering team and drive impactful data solutions.
- Company: Join a cutting-edge AdTech business in London with a hybrid work model.
- Benefits: Competitive salary up to £100,000 and opportunities for professional growth.
- Why this job: Shape the future of analytics and make a real difference in decision-making.
- Qualifications: 6+ years in analytics or data engineering, strong SQL and Python skills required.
- Other info: Fast-paced environment with a focus on innovation and collaboration.
The predicted salary is between 72000 - 84000 £ per year.
Analytics Engineering Manager role leading a growing analytics engineering function at the intersection of data engineering, analytics, product, and advertising performance within an AdTech business. The focus is on turning complex, high-volume data into trusted, scalable analytics that support commercial decision-making. You’ll own the analytics engineering roadmap, lead delivery outcomes, and act as the bridge between technical teams and senior stakeholders, ensuring data is reliable, well-governed, and actionable.
Location: London / Hybrid | Salary: Up to £100,000
Role & Responsibilities- Lead and develop the analytics engineering team, owning delivery quality and outcomes
- Own and execute the analytics engineering roadmap, balancing new capability with technical debt
- Design and evolve ELT pipelines, data warehouse models, and analytical structures
- Ensure reliability and consistency of advertising and performance data across multiple platforms
- Act as the primary interface between engineering, analytics, product, operations, and commercial teams
- Translate business requirements into clear technical plans and priorities
- Define and enforce data governance standards, including testing, documentation, lineage, and observability
- Improve operational efficiency through automation, validation, and anomaly detection
- Maintain hands‑on involvement in critical pipeline design, data modelling, and optimisation work
- Drive continuous improvement across tooling, processes, and team capability
- 6+ years’ experience across analytics engineering, data engineering, or data platform roles
- Proven experience leading and developing technical data teams
- Expert SQL skills and strong Python capability
- Hands‑on experience with dbt (or similar) and modern cloud data warehouses – the preference being BigQuery
- Experience with Looker advantageous
- Strong understanding of advertising and performance data, including measurement and attribution
- Experience building and scaling data governance, testing frameworks, and CI/CD for analytics
- Demonstrated ability to own roadmaps, prioritisation, and delivery in complex environments
- Strong communicator, able to engage both technical teams and senior stakeholders
- Comfortable operating in fast‑paced, cross‑functional environments
Analytics Engineering Manager - Harnham employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineering Manager - Harnham
✨Tip Number 1
Network like a pro! Reach out to folks in the AdTech space, especially those who work in analytics engineering. Use platforms like LinkedIn to connect and engage with them; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! If you've got a portfolio of projects or case studies that demonstrate your expertise in analytics engineering, make sure to share them during interviews. This is your chance to shine and prove you can turn complex data into actionable insights.
✨Tip Number 3
Prepare for the technical interview! Brush up on your SQL and Python skills, and be ready to discuss your experience with ELT pipelines and data governance. We want to see how you can bridge the gap between technical teams and stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Analytics Engineering Manager - Harnham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Analytics Engineering Manager. Highlight your experience in leading analytics engineering teams and your expertise in SQL and Python. We want to see how your skills align with our needs!
Showcase Your Projects: Include specific examples of projects where you've designed ELT pipelines or improved data governance. We love seeing real-world applications of your skills, so don’t hold back on the details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you’re passionate about analytics engineering and how you can bridge the gap between technical teams and stakeholders. We want to feel your enthusiasm for the role!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss any important updates. Plus, it’s super easy!
How to prepare for a job interview at Jobster
✨Know Your Analytics Engineering Roadmap
Before the interview, make sure you understand what an analytics engineering roadmap entails. Be ready to discuss how you would balance new capabilities with technical debt, and share examples from your past experiences where you've successfully owned and executed similar roadmaps.
✨Showcase Your Technical Skills
Brush up on your SQL and Python skills, as these are crucial for the role. Prepare to discuss specific projects where you've designed ELT pipelines or worked with cloud data warehouses like BigQuery. Being hands-on in your examples will demonstrate your capability.
✨Communicate Like a Pro
Since this role requires acting as a bridge between technical teams and senior stakeholders, practice explaining complex technical concepts in simple terms. Think of scenarios where you've had to translate business requirements into technical plans and be ready to share those stories.
✨Emphasise Data Governance Experience
Be prepared to talk about your experience with data governance standards, testing frameworks, and CI/CD processes. Highlight any improvements you've made in operational efficiency through automation or anomaly detection, as this will show your proactive approach to ensuring data reliability.
